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» Modelling Uncertainty in Agent Programming
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ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 13 days ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
78
Voted
ATAL
2008
Springer
15 years 2 months ago
GS3 and Tartanian: game theory-based heads-up limit and no-limit Texas Hold'em poker-playing programs
We demonstrate two game theory-based programs for headsup limit and no-limit Texas Hold'em poker. The first player, GS3, is designed for playing limit Texas Hold'em, in ...
Andrew Gilpin, Tuomas Sandholm, Troels Bjerre S&os...
82
Voted
IAT
2009
IEEE
15 years 7 months ago
Introducing Communication in Dis-POMDPs with Finite State Machines
Distributed Partially Observable Markov Decision Problems (DisPOMDPs) are emerging as a popular approach for modeling sequential decision making in teams operating under uncertain...
Yuki Iwanari, Makoto Tasaki, Makoto Yokoo, Atsushi...
114
Voted
ATAL
2005
Springer
15 years 6 months ago
Bounded model checking for knowledge and real time
We present TECTLK, a logic to specify knowledge and real time in multi-agent systems. We show that the model checking problem is decidable, and we present an algorithm for TECTLK ...
Bozena Wozna, Alessio Lomuscio, Wojciech Penczek
AAAI
2006
15 years 1 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht